Cancer‐Related Pain in Older Adults Receiving Palliative Care: Patient and Family Caregiver Perspectives on the Experience of Pain
Bibliographic record
Abstract
BACKGROUND: Despite an emphasis on pain management in palliative care, pain continues to be a common problem for individuals with advanced cancer. Many of those affected are older due to the disproportionate incidence of cancer in this age group. There remains little understanding of how older patients and their family caregivers perceive patients' cancer-related pain, despite its significance for pain management in the home setting. OBJECTIVES: To explore and describe the cancer pain perceptions and experiences of older adults with advanced cancer and their family caregivers. METHODS: A qualitative descriptive approach was used to describe and interpret data collected from semistructured interviews with 18 patients (≥65 years of age) with advanced cancer receiving palliative care at home and their family caregivers. RESULTS: The main category 'Experiencing cancer pain' incorporated three themes. The theme 'Feeling cancer pain' included the sensory aspects of the pain, its origin and meanings attributed to the pain. A second theme, 'Reacting to cancer pain', included patients' and family caregivers' behavioural, cognitive (ie, attitudes, beliefs and control) and emotional responses to the pain. A third theme, 'Living with cancer pain' incorporated individual and social-relational changes that resulted from living with cancer pain. CONCLUSIONS: The findings provide an awareness of cancer pain experienced by older patients and their family caregivers within the wider context of ongoing relationships, increased patient morbidity and other losses common in the aged.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".